Protein is essential for almost every biological process and the interaction between proteins and their interacting partners play critical roles in the functioning cells. Since mutations that disrupt the protein-protein interactions result in many diseases, it is important to understand the biochemical mechanisms of protein recognition, which is important for deciphering protein interaction network and designing potent drugs with high specificity against protein targets. Our long term goal is to develop theoretical models for describing protein binding specificity and reliably predict protein-protein interactions. In the proposed project, we have the following specific aims. Aim 1, we will develop a computational method that combines computer modeling and bioinformatics analysis to characterize the interaction interface between modular domains and their peptide ligands. We will test this method on several modular domains including SH3, SH2 and PDZ domains that bind to specific peptide sequences. Aim 2, we will systematically predict interacting peptides in the yeast genome of all yeast SH3 domains. Aim 3, we will experimentally validate the predictions in vitro to assess the performance of the computational method. We will also conduct in vivo experiments to examine the biological significance of a set of selected domain-peptide interactions. PUBLIC HEALTH RELEVANCE: Protein-protein interactions play critical roles in the cell and mutations that disrupt these interactions result in many diseases. It is therefore important to understand the biochemical mechanisms of protein recognition.